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nimcet Floating Point Representation PYQ


nimcet PYQ
Suppose we have a 10-bit computer that uses 10-bit floating point computational unit (Float number uses IEEE floating-point arithmetic where a floating point number has 1 sign bit, 5 exponent bits, and 4 fraction bits). The representation for +∞ (plus infinity) is





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Solution

10-bit Floating Point: +∞ Representation

Format: The 10-bit floating point is structured as follows:

  • 1 bit for sign (S)
  • 5 bits for exponent (E)
  • 4 bits for fraction/mantissa (F)

IEEE Rule for +∞:

In IEEE floating-point format, +∞ is represented as:

  • Sign bit (S): 0
  • Exponent bits (E): all 1s → 11111
  • Fraction bits (F): all 0s → 0000

✅ Final 10-bit Representation: 0111110000


nimcet PYQ
The range of the exponent E in the IEEE754 double precision (Binary 64) format is _____





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Solution

✅ IEEE 754 Double Precision Format:

The **exponent** field in the IEEE 754 double precision (Binary 64) format is 11 bits long and uses a **bias of 1023**.

✅ Step-by-Step Explanation:

  • The exponent field has **11 bits**, which means it can represent values between **0 and 2047**.
  • The exponent is stored in **biased form**: the stored value is the actual exponent + 1023.
  • For **normalized numbers**, the exponent range is:
    • Minimum exponent: \( 1 - 1023 = -1022 \)
    • Maximum exponent: \( 2046 - 1023 = +1023 \)
  • Special cases:
    • **Exponent = 0**: Used for **denormalized numbers**.
    • **Exponent = 2047**: Represents **infinity** or **NaN** (Not a Number).

✅ Final Answer:

The range of the exponent E in the IEEE 754 double precision (Binary 64) format is:

From -1022 to +1023 (for normalized numbers)



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